Please use this identifier to cite or link to this item:
https://hdl.handle.net/10356/97401
Title: | Convergence analysis of clipped input adaptive filters applied to system identification | Authors: | Bekrani, Mehdi Khong, Andy Wai Hoong |
Keywords: | DRNTU::Engineering::Electrical and electronic engineering | Issue Date: | 2012 | Conference: | Asilomar Conference on Signals, Systems and Computers (46th : 2012 : Pacific Grove, USA) | Abstract: | One of the efficient solutions for the identification of long finite-impulse response systems is the three-level clipped input LMS/RLS (CLMS/CRLS) adaptive filter. In this paper, we first derive the convergence behavior of the CLMS and CRLS algorithms for both time-invariant and time-varying system identification. In addition, we employ results arising from this analysis to derive the optimal step-size and forgetting factor for CLMS and CRLS. We show that these optimal step-size and forgetting factor allow the algorithms to achieve a low steady-state misalignment. | URI: | https://hdl.handle.net/10356/97401 http://hdl.handle.net/10220/13162 |
DOI: | 10.1109/ACSSC.2012.6489124 | Schools: | School of Electrical and Electronic Engineering | Fulltext Permission: | none | Fulltext Availability: | No Fulltext |
Appears in Collections: | EEE Conference Papers |
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